1
|
|
|
# -*- coding: utf-8 -*- |
2
|
|
|
import datetime as dt |
3
|
|
|
import numpy as np |
4
|
|
|
import pytest |
5
|
|
|
|
6
|
|
|
import eppaurora as aur |
7
|
|
|
|
8
|
|
|
EDISS_FUNCS_EXPECTED = [ |
9
|
|
|
(aur.rr1987, 4.51517584e-07), |
10
|
|
|
(aur.rr1987_mod, 4.75296602e-07), |
11
|
|
|
(aur.fang2008, 4.44256875e-07), |
12
|
|
|
(aur.fang2010_mono, 1.96516057e-007), |
13
|
|
|
(aur.fang2010_maxw_int, 4.41340659e-07), |
14
|
|
|
(aur.fang2013_protons, 4.09444686e-22), |
15
|
|
|
(aur.berger1974, 2.37365609e-03), |
16
|
|
|
] |
17
|
|
|
|
18
|
|
|
|
19
|
|
View Code Duplication |
@pytest.mark.parametrize( |
|
|
|
|
20
|
|
|
"edissfunc, expected", |
21
|
|
|
EDISS_FUNCS_EXPECTED, |
22
|
|
|
) |
23
|
|
|
def test_endiss(edissfunc, expected): |
24
|
|
|
energies = np.logspace(-1, 2, 4) |
25
|
|
|
fluxes = np.ones_like(energies) |
26
|
|
|
# ca. 100, 150, 200 km |
27
|
|
|
scale_heights = np.array([6e5, 27e5, 40e5]) |
28
|
|
|
rhos = np.array([5e-10, 1.7e-12, 2.6e-13]) |
29
|
|
|
# energy dissipation "profiles" |
30
|
|
|
ediss = edissfunc( |
31
|
|
|
energies[None, :], fluxes[None, :], |
32
|
|
|
scale_heights[:, None], rhos[:, None] |
33
|
|
|
) |
34
|
|
|
assert ediss.shape == (3, 4) |
35
|
|
|
np.testing.assert_allclose(ediss[0, 2], expected) |
36
|
|
|
return |
37
|
|
|
|
38
|
|
|
|
39
|
|
View Code Duplication |
@pytest.mark.parametrize( |
|
|
|
|
40
|
|
|
"edissfunc, expected", |
41
|
|
|
# exclude bremsstrahlung for now, |
42
|
|
|
# scipy's rbf interpolation uses np.meshgrid |
43
|
|
|
# which messes with the order of the dimensions |
44
|
|
|
# and doesn't work for higher-dimensional arrays |
45
|
|
|
EDISS_FUNCS_EXPECTED[:-1], |
46
|
|
|
) |
47
|
|
|
def test_endiss_transposed(edissfunc, expected): |
48
|
|
|
energies = np.logspace(-1, 2, 4) |
49
|
|
|
fluxes = np.ones_like(energies) |
50
|
|
|
# ca. 100, 150, 200 km |
51
|
|
|
scale_heights = np.array([6e5, 27e5, 40e5]) |
52
|
|
|
rhos = np.array([5e-10, 1.7e-12, 2.6e-13]) |
53
|
|
|
ediss = edissfunc( |
54
|
|
|
energies[:, None], fluxes[:, None], |
55
|
|
|
scale_heights[None, :], rhos[None, :] |
56
|
|
|
) |
57
|
|
|
assert ediss.shape == (4, 3) |
58
|
|
|
np.testing.assert_allclose(ediss[2, 0], expected) |
59
|
|
|
return |
60
|
|
|
|
61
|
|
|
|
62
|
|
View Code Duplication |
@pytest.mark.parametrize( |
|
|
|
|
63
|
|
|
"edissfunc, expected", |
64
|
|
|
# exclude bremsstrahlung for now, |
65
|
|
|
# scipy's rbf interpolation uses np.meshgrid |
66
|
|
|
# which messes with the order of the dimensions |
67
|
|
|
# and doesn't work for higher-dimensional arrays |
68
|
|
|
EDISS_FUNCS_EXPECTED[:-1], |
69
|
|
|
) |
70
|
|
|
def test_endiss_3d(edissfunc, expected): |
71
|
|
|
energies = np.logspace(-1, 2, 4) |
72
|
|
|
fluxes = np.ones_like(energies) |
73
|
|
|
# ca. 100, 150, 200 km |
74
|
|
|
scale_heights = np.array([6e5, 27e5, 40e5]) |
75
|
|
|
rhos = np.array([5e-10, 1.7e-12, 2.6e-13]) |
76
|
|
|
ediss = edissfunc( |
77
|
|
|
energies[None, None, :], fluxes[None, None, :], |
78
|
|
|
scale_heights[:, None, None], rhos[:, None, None] |
79
|
|
|
) |
80
|
|
|
assert ediss.shape == (3, 1, 4) |
81
|
|
|
np.testing.assert_allclose(ediss[0, 0, 2], expected) |
82
|
|
|
return |
83
|
|
|
|
84
|
|
|
|
85
|
|
View Code Duplication |
@pytest.mark.parametrize( |
|
|
|
|
86
|
|
|
"edissfunc, expected", |
87
|
|
|
# exclude bremsstrahlung for now, |
88
|
|
|
# scipy's rbf interpolation uses np.meshgrid |
89
|
|
|
# which messes with the order of the dimensions |
90
|
|
|
# and doesn't work for higher-dimensional arrays |
91
|
|
|
EDISS_FUNCS_EXPECTED[:-1], |
92
|
|
|
) |
93
|
|
|
def test_endiss_3d_transposed(edissfunc, expected): |
94
|
|
|
energies = np.logspace(-1, 2, 4) |
95
|
|
|
fluxes = np.ones_like(energies) |
96
|
|
|
# ca. 100, 150, 200 km |
97
|
|
|
scale_heights = np.array([6e5, 27e5, 40e5]) |
98
|
|
|
rhos = np.array([5e-10, 1.7e-12, 2.6e-13]) |
99
|
|
|
ediss = edissfunc( |
100
|
|
|
energies[None, :, None], fluxes[None, :, None], |
101
|
|
|
scale_heights[:, None, None], rhos[:, None, None] |
102
|
|
|
) |
103
|
|
|
assert ediss.shape == (3, 4, 1) |
104
|
|
|
np.testing.assert_allclose(ediss[0, 2, 0], expected) |
105
|
|
|
return |
106
|
|
|
|
107
|
|
|
|
108
|
|
|
def test_ssusi_ioniz(): |
109
|
|
|
energies = np.logspace(-1, 2, 4) |
110
|
|
|
fluxes = np.ones_like(energies) |
111
|
|
|
z = np.array([100, 120, 150]) |
112
|
|
|
# energy dissipation "profiles" |
113
|
|
|
ediss = aur.ssusi_ioniz( |
114
|
|
|
z[:, None], |
115
|
|
|
energies[None, :], fluxes[None, :], |
116
|
|
|
) |
117
|
|
|
assert ediss.shape == (3, 4) |
118
|
|
|
return |
119
|
|
|
|